SBIR Phase I: Computer Vision for Merchandizing Forest Products

SBIR 第一阶段：用于林产品商品化的计算机视觉

• 批准号: 2329601
• 负责人: Andrew Henderson
• 金额: $ 27.5万
• 依托单位: HENDTECH LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-02-15 至 2025-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2329601&HistoricalAwards=false
• 关键词: SBIR; Phase; Computer; Vision; Merchandizing

The broader impact of this Small Business Innovation Research (SBIR) Phase I project will result from applying leading-edge artificial intelligence technology to the logging industry. Logging (wood harvesting) is the first step in the production of paper packaging, health and hygiene products, clothing fibers, and even resins that are used in our technology devices. The forest products industry employs nearly one million people and contributes hundreds of billions of dollars to the US economy each year. Yet, there has been very little technological innovation in logging in recent decades. This project aims to research and develop computer vision technology that will augment a person’s ability to grade harvested trees accurately. The resulting technology may increase the number of jobs available to unskilled workers in rural areas, ensure effective and efficient utilization of harvested trees, and increase revenues for thousands of small businesses in the wood supply chain.This Small Business Innovation Research (SBIR) Phase I project aims to demonstrate the feasibility of a computer vision system to augment the skills of human-machine operators in the tasks of grading and sorting logs. During the project, a suitable domain-specific dataset will be established, a new chain of computer vision models will be created and trained, and a fully integrated prototype will be deployed in a remote environment. To achieve these goals, the company will research the use of self-supervised learning to expedite the creation of a domain-specific dataset, along with adaptable chains of models and model compression to enable efficient inference at the logging site (i.e., without the need for cloud computing resources). The company will also create new methods for determining specific objects of interest (such as defects) and assessing the grade of each log. If successful, the project will demonstrate a computer vision system that is able to identify and locate specific logs of interest, track the logs, assess each log’s dimensions, locate defects on the logs, accurately determine a grade for each log, and give visual feedback to a machine operator – all within the operator’s brief decision timeframe.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项小型企业创新研究（SBIR）I阶段项目的更广泛影响将是由于将领先的人工智能技术应用于伐木行业而产生的。伐木（收集木材）是生产纸包装，健康和卫生产品，服装纤维，甚至是我们技术设备中使用的树脂的第一步。森林产品行业的员工近一百万，每年为美国经济贡献了数亿美元。然而，近几十年来，登录的技术创新很少。该项目旨在研究和开发计算机视觉技术，以增强人们准确地对树木进行评分的能力。最终的技术可能会增加粗糙地区的非熟练工人可用的工作数量，确保有效，有效地利用收获的树木，并增加了木材供应链中数千个小型企业的揭示。该小型企业创新研究（SBIR）I阶段项目旨在展示计算机视觉系统的可行性，以增强人体计算机的技能，并分配了划分的人，并分配了成分。在项目期间，将建立一个合适的特定领域数据集，将创建和培训新的计算机视觉模型链，并将完全集成的原型部署在远程环境中。为了实现这些目标，该公司将研究使用自我监督的学习的使用，以加快特定于领域的数据集的创建，以及模型和模型压缩的适应性链条，以在记录网站上有效推理（即，无需云计算资源）。公司还将创建新的方法来确定感兴趣的特定对象（例如缺陷）并评估每个日志的等级。如果成功，该项目将展示一个能够识别和定位感兴趣的特定日志，跟踪日志，评估每个日志维度，在日志上找到缺陷，准确地确定每个日志的缺陷，并向机器操作员提供视觉反馈，并向操作员的简短决策授予NSF的构建范围。影响审查标准。